Unpacking tuples/arrays/lists as indices for Numpy Arrays
I would love to be able to do
>>> A = numpy.array(((1,2),(3,4)))
>>> idx = (0,0)
>>> A[*idx]
and get
1
however this is not valid syntax. Is there a way of doing this without ex开发者_开发技巧plicitly writing out
>>> A[idx[0], idx[1]]
?
EDIT: Thanks for the replies. In my program I was indexing with a Numpy array rather than a tuple and getting strange results. Converting to a tuple as Alok suggests does the trick.
It's easier than you think:
>>> import numpy
>>> A = numpy.array(((1,2),(3,4)))
>>> idx = (0,0)
>>> A[idx]
1
Try
A[tuple(idx)]
Unless you have a more complex use case that's not as simple as this example, the above should work for all arrays.
No unpacking is necessary—when you have a comma between [
and ]
, you are making a tuple, not passing arguments. foo[bar, baz]
is equivalent to foo[(bar, baz)]
. So if you have a tuple t = bar, baz
you would simply say foo[t]
.
Indexing an object calls:
object.__getitem__(index)
When you do A[1, 2], it's the equivalent of:
A.__getitem__((1, 2))
So when you do:
b = (1, 2)
A[1, 2] == A[b]
A[1, 2] == A[(1, 2)]
Both statements will evaluate to True.
If you happen to index with a list, it might not index the same, as [1, 2] != (1, 2)
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